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Learning with Errors is a form of lattice problem used in the design of cryptographic primitives. LWE is based on the Closest Vector Problem (CVP).
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Probability of an RLWE sample
Let $R_q=\mathbb{Z}_q[x]/(x^n+1)$ as usual in the RLWE assumption.
Suppoes that I choose a sample of the RLWE distribution, that is, I compute $(a,y=as+e)$ where $a$ is uniform in $R_q$ and $s,e\lef …
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Hardness of LPN problem with small secret
The Learning Parity with Noise (LPN) assumption states that, for a fixed secret $s$ chosen uniformly from $\{0,1\}^n$, then the distribution that outputs $(a,a\cdot s+e)$, where $a$ is uniform in $\{0 …
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Adapting LWE Trapdoors for Ring-LWE
In the paper Trapdoors for Lattices: Simpler, Tighter, Faster, Smaller by Micciancio and Peikert, they present the following theorem about the existence of trapdoor for LWE. … .$
They mention that the results in the paper can be straightforwardly adapted to the ring setting (Ring-LWE), however, they don't give details on that. …
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Minimum distance between polynomials in ring-LWE
Let $R_q=\mathbb{Z}_q[x]/\langle f(x)\rangle$ where $f(x)=x^n+1$, as in the ring-LWE problem.
Let $a(x)$ be chosen uniformly at random from $R_q$. …